Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 4 years of experience in product management, consulting, co-founder or related technical role.
- 2 years of experience building and shipping technical products.
Preferred qualifications:
- Master's degree or PhD in a technical field.
- Experience training, fine tuning, and deploying large language models.
- Experience with machine learning news from conferences (e.g., NeurIPS, ICML, and ICLR).
- Experience within Cloud Infrastructure (e.g., compute, networking, storage).
- Experience with narrative and storytelling to promote usage and adoption.
About the job
At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.
In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.
One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.
Google’s Machine Learning, Systems, and Cloud AI (MSCA) organization builds the technical foundation behind Google’s products as well as for Google Cloud’s compute and AI/ML offerings. The team manages the underlying design elements, developer platforms, product components, and infrastructure at Google. Core ML is the central platform team that provides ML software tools, services, solutions, and infrastructure to all the Google product areas, including Search, Ads, YouTube, Cloud, Maps, and more. Core ML is focused on Driving ML. The goal is to make it easier to perform ML experimentation, development, and productionization, as well as work with Google Research to bring new ML models and innovation across the stack to market.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
The US base salary range for this full-time position is $142,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Develop an idea for Google’s large model infrastructure with efficiency and scaling.
- Identify opportunities to improve the efficiency of training, serving, and fine tuning workloads.
- Manage hardware and software development programs to enable productive use of the systems as deployed.
- Develop partnerships with Google’s product areas and understand evolving needs for Generative AI training and serving. Help understand and improve developer experiences, and enable productive use of Google’s ML resources.
- Own and set the strategy, roadmap, and implementation for multiple areas of focus, balancing short- and long-term priorities against various business needs.
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